Field of the Invention
Embodiments of the disclosure relate to computer graphics. More specifically, embodiments disclosed herein relate to compressing deep images using Lie algebras.
Description of the Related Art
Generally, in computer graphics, colors are represented by red green blue alpha (RGBA) values per pixel. An image may be represented by an array of RGBA values. In such implementations, the red, green, and blue values represent the respective intensities of the primary red, green, and blue colors, which, when added together, produce a color. The alpha value represents the opacity of the pixel, or how much of the background is obscured (where, for example, on a scale of zero to one, an alpha value of zero means a pixel is fully transparent, and an alpha value of one means the pixel is opaque). Stated differently, the pixel value can be considered to be a pair of channels A=[a, α], where a is the amount of new light emitted from A, and a is the amount of light that A blocks from shining through it from outside sources. The quantity a may either be an RGB vector, or a scalar representing monochrome intensity. A pixel blocks no incoming light (or is transparent) when α=0, and blocks all of the light (or is opaque) when α=1.
The alpha values facilitate digital image compositing, which is a component of computer graphics technology. Generally, compositing is the combining of different visual elements into a single image (or single frame of a video). Stated differently, composting facilitates layering of different images or objects together into a composite image. By providing alpha values, computer graphics rendering engines are able to determine what objects should be visible when an image (or scene) is rendered. For example, a fully opaque object may obscure objects that are occupying the same 2-dimensional space.
However, conventional compositing techniques traditionally require the depth ordering of each visual element (e.g., each image being composited, or elements thereof) to be known a priori. In particular, conventional compositing techniques have no intrinsic way to deal with elements whose depth order may vary from pixel to pixel. Even more problematic are volumetric elements such as clouds, whose emission and attenuation may occupy extended depth regions. Combining two clouds requires computing new pixel values for regions that overlap in depth, something that conventional compositing techniques cannot compute directly. Therefore, for some objects such as clouds, murky water, and cloudy glass, conventional compositing techniques do not produce optimal results.